Risk-Averse Resilient Operation of Electricity Grid Under the Risk of Wildfire

Abstract

Wildfires and other extreme weather conditions due to climate change are stressing the aging electrical infrastructure. Power utilities have implemented public safety power shutoffs as a method to mitigate the risk of wildfire by proactively de-energizing some power lines, which leaves customers without power. System operators have to make a compromise between de-energizing of power lines to avoid the wildfire risk and energizing those lines to serve the demand. In this work, with a quantified wildfire ignition risk of each line, a resilient operation problem is presented in power systems with a high penetration level of renewable generation resources. A two-stage robust optimization problem is formulated and solved using column-and-constraint generation algorithm to find improved balance between the de-energization of power lines and the customers served. Different penetration levels of renewable generation to mitigate the impact of extreme fire hazard situations on the energization of customers is assessed. The validity of the presented robust optimization algorithm is demonstrated on various test cases.

Figures (7)

• Figure 1: Different wind speeds leading to different fire ignition scores in a 6-bus test case
• Figure 2: Flowchart of Column-and-Constraint Generation Algorithm
• Figure 3: Impact of risk tolerance on the operation cost under different budget of uncertainties in 6-bus test case
• Figure 4: Change in operation cost based on budget of uncertainty when $\mathcal{E}=0.1$ and different deviations are considered in 6-bus test case
• Figure 5: Impact of different levels of solar penetration on the operation cost in 6-bus test case